In quantum mechanics (physics), there is a principle known as Heisenberg’s Uncertainty Principle. It states that when observing sub-atomic particles, “the more precisely the position is determined, the less precisely the momentum is known in this instant.” In simple terms, you can’t know everything about what you are observing because the world you are observing is always changing. Once you try to precisely measure something, it is no longer the exact same something you were measuring a moment ago. While Heisenberg was speaking about particles that make up atoms, he argued that the idea of uncertainty could have much larger implications on the macroscopic world. He applied this to nature as well and argued that we can predict the probable future based on evidence at hand but there is always an aspect of uncertainty present in nature, thus we cannot predict with absolute certainty the result of anything we do.
If you hadn’t already guessed, I’m a scientist at heart. I believe in sound scientific research and that the advancements in science, medicine, and technology have brought about changes that indeed improve our safety and health. Technological advancements have contributed to the reduced number of deaths in motor vehicle accidents by putting safety features such as side impact air bags, seat belts, and improved structural design in cars. Advancements in medicine have provided microsurgery and organ transplants to children and saved these precious little people who otherwise may not have had a fighting chance at life. Even for those of us who are more holistic minded, science has allowed us to identify which vitamins and herbals are beneficial for certain ailments and provided them to consumers in easy to use formulas.
How have all of these advancements come about? Empirical research using the well respected “scientific method.” The scientific method is thought to be the best way to approach research: make observations, develop a hypothesis, design an experiment to test the hypothesis, test the hypothesis, accept or reject the hypothesis, modify the hypothesis, rinse and repeat. Nowadays, scientists and doctors alike often do this many times before they are able to confirm or discard their hypothesis. Empirically sound research also has a “control” group which does not receive whatever “treatment” was being tested for efficacy. This control group is used to compare to the treatment group. Researchers will also often use blind or double blind studies (a technician administers treatment and does not know if the treatment is a placebo or the real treatment) and then the researchers only see the data. This eliminates the possibility that data and conclusions can be influenced by the researcher’s bias or desire to see a treatment succeed. This is especially important in medical and pharmaceutical studies because the researcher needs to be able to prove without a doubt that improvement in a patient’s health is due to the actual treatment being tested, rather than outside influences such as the “placebo effect.”
Once someone has a research study that has important implications, he will submit the study to a peer-reviewed journal. These journals (like the American Journal of Medicine) have a board of people knowledgeable about the main topic of the journal (medicine, psychiatry, physics, ect.) The board reviews the research study to determine if it was done with professionalism and respect for the scientific method, ethical concerns, and if the conclusions drawn as a result of the study make sense. These journals are in databases across the internet, available to people with certain credentials and often for a price. College students also have access (through their college’s library) to many of these journals for their own research and educational purposes. These journals essentially serve as the primary resource for current and widely respected scientific information about the specific area of focus for which the journal is dedicated.
Good research also reports any and all side effects of whatever treatment was tested. If one person gets hit by a bus while in a drug trial and dies, it is still reported as a death in the trial. Everything that happens is recorded and reported so that the researchers can allow consumers to know that while they may not be able to tell you why (if it was the result of the treatment or other unknown factors) a person experienced frequent migraines while on this medication, frequent migraines were reported while on this medication. The information is there for the doctors and consumers to decide if the risks of a specific treatment outweigh the benefits or vice versa.
So what does this have to do with birth?
I know, you’re wondering what the heck this has to do with anything and why this is on The Birthing Site. Among the natural birthing community, there are a number of widely held beliefs that don’t necessarily have tons of scientific research to back them up. Nonetheless, these beliefs are logical, and often backed up by thousands of years of natural birthing women’s experiences and the modern day experiences of midwives. You may actually find OB’s who agree with these practices, but don’t often educate their patients about them because birthing policies are often instituted by the legal staff for convenience. That being said, many OBs are reluctant to take a more “hands off” approach to labor and delivery and insist on things like fetal monitoring, vitamin K shots, suctioning and immediate cord clamping due to the presumed safety of these procedures and the possibility of eliminating the risks which these procedures are designed to prevent.
So back to research: let’s take for example the connection between epidurals and c-sections. In 2008, approximately 60% of women in the U.S. receive an epidural during labor (many hospitals report rates as high as 90%), and in 2009 our national c-section rate was 33%. Infant mortality rates in the US are also higher than most other developed countries in the world. The WHO’s recommended c-section rate is 15% or below, and the U.S. has one of the highest c-section rates among developed countries. These statistics don’t seem to reflect our advanced medicine and technology.
Do a quick Google search and you’ll find about a zillion pages of people quoting research that declares “epidurals don’t cause c-sections and can’t be blamed for increased c-section rates.” There is a boatload of seemingly trustworthy research that supposedly debunks the idea that having an epidural increases your chances of having a c-section. Here is the problem; much of this “research” was conducted in real time: real women in real labor. The doctors who determined who needed a c-section and who had the chance to labor longer knew which women had epidurals. There is no way to do true empirical research on such an unpredictable process as birth.
So what about statistics? I have a love hate relationship with statistics. While I’d swear that I owe my just barely passing grade in statistics to a professor who gave me points for effort, there are one or two things I did learn and still remember. First, correlation is not causation. The increase in the use of epidurals may not be the primary cause for the increase in the c-section rate; however, this relationship should not be ignored. More importantly though, anyone with motivation can get statistics to back up their claim and make it look convincing, it’s all in the math. The phrase “statistically significant” is tossed around a great deal in research studies but most people don’t understand what this really means. We hear a technical term like this and assume it must be important. The truth is that it is important to a point. Statistical significance is a mathematical assessment of the data that will allow a researcher to determine if the effect of a treatment is due to chance/outside factors, or more likely due to the treatment itself. Here’s a little secret though, the statistical significance part of the math is determined by the researcher. While the researcher has the responsibility to report this value in their research write up, the general public will rarely ever read this, much less bother trying to understand the math. Thus a researcher who has data that doesn’t really support his hypothesis could in theory change the statistical significance value for the mathematical part of the data analysis which could make it look more meaningful than it did before.
Let’s use another example for this: the claim that circumcision reduces the chances of contracting STD’s including HIV. Many of these studies were done in third world countries where medicine is hard to come by, and condoms are even more rare. So a bunch of doctors swoop in to save these people by circumcising the men and then say “hey the rates of STD and HIV transmission are significantly lower.” But what do they mean by significant? How can you even test for that? You would have to look at statistics in the long term (over a period of years) or design a study.
A study might look like this: 100 men who were not circumcised had sex once with a woman who is known to have HIV and 50 of them got HIV. Another 100 men were circumcised and had sex once with a woman who was known to have HIV and only 10 of them contracted HIV, does that mean circumcision alone reduced your chances of getting HIV to 10% from 50%? Of course due to the ethical implications involved this would never actually be a real study, but for illustration purposes, let’s discuss the other problems with this. Did anyone use a condom? Were these men educated on safe sex practices and given high quality latex condoms and before being circumcised? How long did the woman who has HIV have it for? Was she symptomatic? What was the men’s current state of health? There are so many things that could potentially contribute to the transmission of HIV, and most of the studies that declare circumcision as a means to reduce the transmission of HIV don’t address the human factor.
Let’s be honest here, if an uncircumcised man has unprotected sex with many partners who also have a history of unprotected sex with many partners, he’s probably going to catch something. Likewise, if a circumcised man is careful about whom he has sex with, always uses condoms, and does not have numerous partners; he’s less likely to catch something than the first man.
The real truth is that with all the advancements of science and medicine, there are some things in nature that are both unpredictable and better left alone. Birth is one of these things. While there are certain circumstances where medicine and technology may provide life saving care to the mother and baby, these circumstances are usually in higher risk pregnancies. The c-section, infant and mother mortality rates for midwives are insanely low, in fact they are lower (by a substantial margin) than nearly any OB and hospital. The truth is that we can’t use scientific research and data to predict how things will be, nor what method of intervention is “the best” or the least risky. The truth is that long term studies of the effects of vaccines on children, of epidural medication on mothers and children, and of c-section rates on bonding and breastfeeding are virtually impossible to do for two reasons. First, you can’t really follow someone, much less a group of people for their entire life and record everything about their health and mental status. Secondly, the more we interact with the world, the more uncertain the cause and effect relationship becomes. Did this child develop autism because of a vaccine related issue, because his mother was exposed to a chemical during her pregnancy, or maybe he was exposed to something in the hospital or his home as a newborn? Did this adult develop an auto-immune disease such as Lupus because she received too many vaccines as a baby, or was she just more susceptible to certain chemicals in her environment?
The more we have developed ways to facilitate, speed up, and control risks in labor, the more interventions we have developed to counteract the side effects of the initial interventions. An OB may break a woman’s water to start labor and give her pitocin the next day because she didn’t begin to have contractions and is now at risk of infection. She may begin to have intense contractions and ask for an epidural. She may labor for many more hours once her epidural kicks in because it slowed labor. She may be exhausted and not able to feel anything below her waist and her baby may be in distress and she may then require a c-section. Was it the epidural that caused the c-section? Maybe it was the pitocin that caused her to have intense contractions leading to her exhaustion. What about the OB that broke her water because she was 39 weeks along and hadn’t gone into labor yet? Did the OB tell her what might happen if labor didn’t start on its own? Did she even know to ask?
Research gives us a starting point for information, but it should be simply a way to facilitate your own research and thinking about what is right for you and your baby. Research may show that there are minimal risks to a given procedure or treatment, but it can’t account for the human factor; nothing is ever completely certain. Long term side effects and risks are virtually impossible to test for, but we do know that the less junk we put in our bodies, the more likely we are to maintain our health. The same goes for birth; the less we try to intervene, the more likely a positive outcome will be. Let’s face it, the human race didn’t survive for thousands of years because birth was risky and women and babies died all the time. If that was true, we wouldn’t be here with our laptops, energy supplements, and epidurals.
In closing I leave you with this quote from Heisenberg: “Natural science does not simply describe or explain nature, it is part of the interplay between nature and ourselves.”